Using ultrasound and artificial intelligence to assess muscle stretch reflexes

ABSTRACT

The present disclosure provides using ultrasound technology and artificial intelligence to enhance MSR assessment by making the assessment more objective, reproducible, and recordable to allow a more precise and/or personalized approach to the medical practice of individual patients via using multiple ultrasound functions and artificial intelligence to improve the accuracy and consistency of assessing reflexes and allowing MSR data to be combined with other patient medical information for improved diagnosis and management of a patient&#39;s condition.

TECHNICAL FIELD

The present disclosure relates to employing ultrasound technology andartificial intelligence to improve MSR assessment, making same moreobjective, reproducible, and recordable.

BACKGROUND

Assessing muscle stretch reflexes (MSRs), more commonly known as deeptendon reflexes (DTRs), with a reflex hammer has been an importantcomponent of the comprehensive physical examination for over 150 years.There are six commonly recognized MSRs with the “knee jerk” being themost widely recognized example. The stretch reflex, or more accurately“muscle stretch reflex”, is a muscle contraction in response tostretching within the muscle. The reflex functions to maintain themuscle at a constant length.

In brief, a MSR occurs when stretch receptors within a muscle areactivated when the muscle is lengthened or stretched usually by theexaminer tapping on the muscle tendon with a reflex hammer. This tapactivates stretch receptors in the muscle spindle sending a sensorynerve impulse to a connection or synapse in the spinal cord to a motorneuron that sends an impulse back to the muscle leading to musclecontraction and the characteristic jerk of the limb being tested.

For the knee jerk, this means tapping on the patellar tendon with thereflex hammer that stretches the quadricep muscle sending a sensorysignal to the spine that synapses with the motor neuron sending a motorsignal back to the quadriceps muscle activating contraction and thecharacteristic knee jerk or brisk forward motion of the lower leg. Whilethis process takes place, an inhibitory neural signal is sent to theopposing muscle generally on the opposite side of the joint and, in thiscase, the muscle opposing the quadriceps is the hamstring which isinhibited from contracting.

This local level (lower motor neuron) control of MSRs is also influencedby the neurological system higher up in the spinal cord and brain (uppermotor neuron) which is typically inhibitory. If the inhibitory controlis lost, the reflex can become greater than normal or hyper-reflexive.Thus, there are multiple components to MSRs including the muscle itself,peripheral nerves, the spinal cord, and the brain. In addition, thechemical and electrical activity of the muscles and nerves responsiblefor contraction can be affected by abnormalities in the level ofelectrolytes, such as calcium and magnesium, and any toxins in the body.

MSRs in the normal physiological state should be symmetrical from oneside of the body to the other. In other words, the degree of knee jerkin the right knee should be approximately the same as that in the leftknee. Asymmetry in response would raise the possibility of an underlyingpathological process. In addition, MSR results in a patient must alwaysbe considered in the larger context of the patient's health, otherphysical examination findings, laboratory results, imaging results, andmedical conditions.

Accurate and consistent assessment of MSRs provide important clinicalinformation in diagnosing and managing many medical conditions. Besidesthe more direct neuromuscular conditions such as spinal cord injury,neurodegenerative diseases, myopathies, and strokes, MSRs are used toevaluate many everyday medical conditions such as a herniated disc inthe lower back causing sciatica, assessment for neuropathy in a diabeticpatient, hypothyroidism, and eclampsia in a pregnant patient.

Presently, the assessment of MSRs is highly subjective on the part ofthe examining practitioner, which includes many specialty andsubspecialty physicians, nurses, nurse practitioners, physicalassistants, and other health care providers. The examiner strikes themuscle tendon with a reflex hammer or other object and estimates thedegree of response on a scale from zero to four with zero being noreflex and four being a hyperactive reflex. A reflex of 2 is considerednormal. A more detailed scale of assessment is often used by adding aplus or minus to the number such as 2+ for slightly greater than normalor 2− for slightly less than normal. It is understood that reflexes canvary between individuals with a range of 1 to 3 possibly being normalfor a particular individual.

An examiner's assessment of a patient's reflex is highly dependent onpersonal experience and skill in performing the examination. Patientcharacteristics can affect performing the examination such as bodyhabitus and the patient's ability to fully participate in theexamination which requires the appropriate joint position, relaxation,and following commands.

Accordingly, it is an object of the present disclosure to provide a morecomprehensive as well as repeatable method of conducting MSRassessments. Herein, using ultrasound technology and artificialintelligence will make MSR assessment more objective, reproducible, andrecordable.

Citation or identification of any document in this application is not anadmission that such a document is available as prior art to the presentdisclosure.

SUMMARY

The above objectives are accomplished according to the presentdisclosure by providing in one embodiment, a method for improved musclestretch reflex assessments. The method may include eliciting at leastone muscle stretch reflex response in a subject, employing at least oneultrasound function to analyze the subject while the muscle stretchreflex response occurs, obtaining muscle stretch reflex data regardingthe at least one muscle stretch reflex response for the subject, andanalyzing the muscle stretch reflex data to determine a health conditionof the subject. Further, the muscle stretch reflex data obtained fromthe subject may be recorded. Again, artificial intelligence may be usedto analyze the muscle stretch reflex data. Still, a medical conditionmay be diagnosed as indicated via the muscle stretch reflex dataobtained from the subject. Moreover, the muscle stretch reflex data maybe combined with at least one other neuromuscular assessment data. Yetagain, the at least one other neuromuscular assessment data may compriseperipheral nerve conduction velocities, electro-myography,tensiomyography, or magnetic resonant imaging. Still further, the musclestretch reflex data may be analyzed in conjunction with analyzinggenetic information of the subject. Further still, the muscle stretchreflex data may be employed to manage a medical condition in thesubject. Furthermore, the ultrasound function may analyze the subjectprior to, during, and after elicitation of the muscle stretch reflexresponse. Yet further, the method may include measuring presence andmagnitude of the muscle stretch reflex response.

In an alternative embodiment, a new ultrasound analysis technique isprovided. The technique can include eliciting at least one musclestretch reflex response in a subject, employing an ultrasound device ineither A Mode, B Mode, M Mode or Doppler Mode to analyze the subjectwhile the muscle stretch reflex response occurs, obtaining musclestretch reflex data regarding the at least one muscle stretch reflexresponse for the subject, and analyzing the muscle stretch reflex datato determine a health condition of the subject. Further, the musclestretch reflex data obtained from the subject may be recorded. Still,artificial intelligence may analyze the muscle stretch reflex data.Moreover, a medical condition indicated via the muscle stretch reflexdata obtained from the subject may be diagnosed. Yet again, the musclestretch reflex data may be combined with at least one otherneuromuscular assessment data. Still again, the at least one otherneuromuscular assessment data may include peripheral nerve conductionvelocities, electro-myography, tensiomyography, or magnetic resonantimaging. Moreover, the muscle stretch reflex data may be analyzed inconjunction with genetic information of the subject. Further again, themuscle stretch reflex data may be employed to manage a medical conditionin the subject. Yet again, the ultrasound device may analyze the subjectprior to, during, and after elicitation of the muscle stretch reflexresponse. Still further, the technique may include measuring presenceand magnitude of the at least one muscle stretch reflex response byanalyzing muscle size changes during the at least one muscle stretchreflex response.

These and other aspects, objects, features, and advantages of theexample embodiments will become apparent to those having ordinary skillin the art upon consideration of the following detailed description ofexample embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

An understanding of the features and advantages of the presentdisclosure will be obtained by reference to the following detaileddescription that sets forth illustrative embodiments, in which theprinciples of the disclosure may be utilized, and the accompanyingdrawings of which:

FIG. 1 shows a photograph of an ultrasound scanning probe in transverseposition over the rectus femoris and vastus intermedius of thequadriceps muscle while tapping the patella tendon with a reflex hammerwith the probe in transverse (a) and longitudinal (b) positions.

FIG. 2 transverse view of B-mode identifying rectus femoris and vastusintermedius.

FIG. 3 spectral Doppler-mode scanning the vastus intermedius, a chirpingsound with biphasic or triphasic waveform.

FIG. 4 shows Doppler-mode—putting the scan line in the middle of vastusintermedius, dipping with gradual return to the baseline due tocontraction of muscle.

FIG. 5 shows M-mode wherein the scanline is in the middle of the vastusintermedius dipping with gradual return to the baseline due tocontraction of muscle.

FIG. 6 shows M-mode calculating the speed of contraction of muscles.

FIG. 7 shows B-mode used to measure muscle size change from restingstate to contraction during reflex response.

FIG. 8 shows M-mode assessment of vastus intermedius in resting stateand then contraction during reflex response in the longitudinal view.

The figures herein are for illustrative purposes only and are notnecessarily drawn to scale.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

Before the present disclosure is described in greater detail, it is tobe understood that this disclosure is not limited to particularembodiments described, and as such may, of course, vary. It is also tobe understood that the terminology used herein is for the purpose ofdescribing particular embodiments only, and is not intended to belimiting.

Unless specifically stated, terms and phrases used in this document, andvariations thereof, unless otherwise expressly stated, should beconstrued as open ended as opposed to limiting. Likewise, a group ofitems linked with the conjunction “and” should not be read as requiringthat each and every one of those items be present in the grouping, butrather should be read as “and/or” unless expressly stated otherwise.Similarly, a group of items linked with the conjunction “or” should notbe read as requiring mutual exclusivity among that group, but rathershould also be read as “and/or” unless expressly stated otherwise.

Furthermore, although items, elements or components of the disclosuremay be described or claimed in the singular, the plural is contemplatedto be within the scope thereof unless limitation to the singular isexplicitly stated. The presence of broadening words and phrases such as“one or more,” “at least,” “but not limited to” or other like phrases insome instances shall not be read to mean that the narrower case isintended or required in instances where such broadening phrases may beabsent.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this disclosure belongs. Although any methods andmaterials similar or equivalent to those described herein can also beused in the practice or testing of the present disclosure, the preferredmethods and materials are now described.

All publications and patents cited in this specification are cited todisclose and describe the methods and/or materials in connection withwhich the publications are cited. All such publications and patents areherein incorporated by references as if each individual publication orpatent were specifically and individually indicated to be incorporatedby reference. Such incorporation by reference is expressly limited tothe methods and/or materials described in the cited publications andpatents and does not extend to any lexicographical definitions from thecited publications and patents. Any lexicographical definition in thepublications and patents cited that is not also expressly repeated inthe instant application should not be treated as such and should not beread as defining any terms appearing in the accompanying claims. Thecitation of any publication is for its disclosure prior to the filingdate and should not be construed as an admission that the presentdisclosure is not entitled to antedate such publication by virtue ofprior disclosure. Further, the dates of publication provided could bedifferent from the actual publication dates that may need to beindependently confirmed.

As will be apparent to those of skill in the art upon reading thisdisclosure, each of the individual embodiments described and illustratedherein has discrete components and features which may be readilyseparated from or combined with the features of any of the other severalembodiments without departing from the scope or spirit of the presentdisclosure. Any recited method can be carried out in the order of eventsrecited or in any other order that is logically possible.

Where a range is expressed, a further embodiment includes from the oneparticular value and/or to the other particular value. The recitation ofnumerical ranges by endpoints includes all numbers and fractionssubsumed within the respective ranges, as well as the recited endpoints.Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimit of that range and any other stated or intervening value in thatstated range, is encompassed within the disclosure. The upper and lowerlimits of these smaller ranges may independently be included in thesmaller ranges and are also encompassed within the disclosure, subjectto any specifically excluded limit in the stated range. Where the statedrange includes one or both of the limits, ranges excluding either orboth of those included limits are also included in the disclosure. Forexample, where the stated range includes one or both of the limits,ranges excluding either or both of those included limits are alsoincluded in the disclosure, e.g. the phrase “x to y” includes the rangefrom ‘x’ to ‘y’ as well as the range greater than ‘x’ and less than ‘y’.The range can also be expressed as an upper limit, e.g. ‘about x, y, z,or less’ and should be interpreted to include the specific ranges of‘about x’, ‘about y’, and ‘about z’ as well as the ranges of ‘less thanx’, less than y′, and ‘less than z’. Likewise, the phrase ‘about x, y,z, or greater’ should be interpreted to include the specific ranges of‘about x’, ‘about y’, and ‘about z’ as well as the ranges of ‘greaterthan x’, greater than y′, and ‘greater than z’. In addition, the phrase“about ‘x’ to ‘y’”, where ‘x’ and ‘y’ are numerical values, includes“about ‘x’ to about ‘y’”.

It should be noted that ratios, concentrations, amounts, and othernumerical data can be expressed herein in a range format. It will befurther understood that the endpoints of each of the ranges aresignificant both in relation to the other endpoint, and independently ofthe other endpoint. It is also understood that there are a number ofvalues disclosed herein, and that each value is also herein disclosed as“about” that particular value in addition to the value itself. Forexample, if the value “10” is disclosed, then “about 10” is alsodisclosed. Ranges can be expressed herein as from “about” one particularvalue, and/or to “about” another particular value. Similarly, whenvalues are expressed as approximations, by use of the antecedent“about,” it will be understood that the particular value forms a furtheraspect. For example, if the value “about 10” is disclosed, then “10” isalso disclosed.

It is to be understood that such a range format is used for convenienceand brevity, and thus, should be interpreted in a flexible manner toinclude not only the numerical values explicitly recited as the limitsof the range, but also to include all the individual numerical values orsub-ranges encompassed within that range as if each numerical value andsub-range is explicitly recited. To illustrate, a numerical range of“about 0.1% to 5%” should be interpreted to include not only theexplicitly recited values of about 0.1% to about 5%, but also includeindividual values (e.g., about 1%, about 2%, about 3%, and about 4%) andthe sub-ranges (e.g., about 0.5% to about 1.1%; about 5% to about 2.4%;about 0.5% to about 3.2%, and about 0.5% to about 4.4%, and otherpossible sub-ranges) within the indicated range.

As used herein, the singular forms “a”, “an”, and “the” include bothsingular and plural referents unless the context clearly dictatesotherwise.

As used herein, “about,” “approximately,” “substantially,” and the like,when used in connection with a measurable variable such as a parameter,an amount, a temporal duration, and the like, are meant to encompassvariations of and from the specified value including those withinexperimental error (which can be determined by e.g. given data set, artaccepted standard, and/or with e.g. a given confidence interval (e.g.90%, 95%, or more confidence interval from the mean), such as variationsof +/−10% or less, +/−5% or less, +/−1% or less, and +/−0.1% or less ofand from the specified value, insofar such variations are appropriate toperform in the disclosure. As used herein, the terms “about,”“approximate,” “at or about,” and “substantially” can mean that theamount or value in question can be the exact value or a value thatprovides equivalent results or effects as recited in the claims ortaught herein. That is, it is understood that amounts, sizes,formulations, parameters, and other quantities and characteristics arenot and need not be exact, but may be approximate and/or larger orsmaller, as desired, reflecting tolerances, conversion factors, roundingoff, measurement error and the like, and other factors known to those ofskill in the art such that equivalent results or effects are obtained.In some circumstances, the value that provides equivalent results oreffects cannot be reasonably determined. In general, an amount, size,formulation, parameter or other quantity or characteristic is “about,”“approximate,” or “at or about” whether or not expressly stated to besuch. It is understood that where “about,” “approximate,” or “at orabout” is used before a quantitative value, the parameter also includesthe specific quantitative value itself, unless specifically statedotherwise.

The term “optional” or “optionally” means that the subsequent describedevent, circumstance or substituent may or may not occur, and that thedescription includes instances where the event or circumstance occursand instances where it does not.

The terms “subject,” “individual,” and “patient” are usedinterchangeably herein to refer to a vertebrate, preferably a mammal,more preferably a human. Mammals include, but are not limited to,murines, simians, humans, farm animals, sport animals, and pets.Tissues, cells and their progeny of a biological entity obtained in vivoor cultured in vitro are also encompassed by the term “subject”.

As used interchangeably herein, the terms “sufficient” and “effective,”can refer to an amount (e.g. mass, volume, dosage, concentration, and/ortime period) needed to achieve one or more desired and/or statedresult(s). For example, a therapeutically effective amount refers to anamount needed to achieve one or more therapeutic effects.

As used herein, “tangible medium of expression” refers to a medium thatis physically tangible or accessible and is not a mere abstract thoughtor an unrecorded spoken word. “Tangible medium of expression” includes,but is not limited to, words on a cellulosic or plastic material, ordata stored in a suitable computer readable memory form. The data can bestored on a unit device, such as a flash memory or CD-ROM or on a serverthat can be accessed by a user via, e.g. a web interface.

As used herein, “therapeutic” can refer to treating, healing, and/orameliorating a disease, disorder, condition, or side effect, or todecreasing in the rate of advancement of a disease, disorder, condition,or side effect. A “therapeutically effective amount” can therefore referto an amount of a compound that can yield a therapeutic effect.

As used herein, the terms “treating” and “treatment” can refer generallyto obtaining a desired pharmacological and/or physiological effect. Theeffect can be, but does not necessarily have to be, prophylactic interms of preventing or partially preventing a disease, symptom orcondition thereof, such as cancer and/or indirect radiation damage. Theeffect can be therapeutic in terms of a partial or complete cure of adisease, condition, symptom or adverse effect attributed to the disease,disorder, or condition. The term “treatment” as used herein covers anytreatment of cancer and/or indirect radiation damage, in a subject,particularly a human and/or companion animal, and can include any one ormore of the following: (a) preventing the disease or damage fromoccurring in a subject which may be predisposed to the disease but hasnot yet been diagnosed as having it; (b) inhibiting the disease, i.e.,arresting its development; and (c) relieving the disease, i.e.,mitigating or ameliorating the disease and/or its symptoms orconditions. The term “treatment” as used herein can refer to boththerapeutic treatment alone, prophylactic treatment alone, or boththerapeutic and prophylactic treatment. Those in need of treatment(subjects in need thereof) can include those already with the disorderand/or those in which the disorder is to be prevented. As used herein,the term “treating”, can include inhibiting the disease, disorder orcondition, e.g., impeding its progress; and relieving the disease,disorder, or condition, e.g., causing regression of the disease,disorder and/or condition. Treating the disease, disorder, or conditioncan include ameliorating at least one symptom of the particular disease,disorder, or condition, even if the underlying pathophysiology is notaffected, such as treating the pain of a subject by administration of ananalgesic agent even though such agent does not treat the cause of thepain.

Various embodiments are described hereinafter. It should be noted thatthe specific embodiments are not intended as an exhaustive descriptionor as a limitation to the broader aspects discussed herein. One aspectdescribed in conjunction with a particular embodiment is not necessarilylimited to that embodiment and can be practiced with any otherembodiment(s). Reference throughout this specification to “oneembodiment”, “an embodiment,” “an example embodiment,” means that aparticular feature, structure or characteristic described in connectionwith the embodiment is included in at least one embodiment of thepresent disclosure. Thus, appearances of the phrases “in oneembodiment,” “in an embodiment,” or “an example embodiment” in variousplaces throughout this specification are not necessarily all referringto the same embodiment, but may. Furthermore, the particular features,structures or characteristics may be combined in any suitable manner, aswould be apparent to a person skilled in the art from this disclosure,in one or more embodiments. Furthermore, while some embodimentsdescribed herein include some but not other features included in otherembodiments, combinations of features of different embodiments are meantto be within the scope of the disclosure. For example, in the appendedclaims, any of the claimed embodiments can be used in any combination.

All patents, patent applications, published applications, andpublications, databases, websites and other published materials citedherein are hereby incorporated by reference to the same extent as thougheach individual publication, published patent document, or patentapplication was specifically and individually indicated as beingincorporated by reference.

Kits

Any of the methods described herein can be presented as a combinationkit. As used herein, the terms “combination kit” or “kit of parts”refers to the methods, techniques, analysis functions, AI analysis, andany additional components that are used to package, sell, market,deliver, and/or administer the methods and techniques described herein.Such additional components include, but are not limited to, packaging,ultrasound devices, muscle stretch reflex “triggering” instruments suchas hammers, etc., blister packages and the like. When the methods andtechniques described herein or a combination thereof and/or kitcomponents are not administered simultaneously, the combination kit cancontain each various equipment for performing the muscle stretch reflexand analysis in separate combinations and/or packages. The separate kitcomponents can be contained in a single package or in separate packageswithin the kit.

In some embodiments, the combination kit also includes instructionsprinted on or otherwise contained in a tangible medium of expression.The instructions can provide information regarding eliciting, analyzing,recording, analyzing muscle stretch data with AI, safety information,information regarding medical analysis of various medical conditions,indications for use, and/or recommended treatment regimen(s) for themethods and techniques contained/described therein. In some embodiments,the instructions can provide directions and protocols for administeringmuscle stretch reflex tests and obtaining data from same from a subject.In some embodiments, the instructions can provide one or moreembodiments of the methods and/or techniques such as any of the methodsdescribed in greater detail elsewhere herein.

A recorded objective measure of a particular patient's MSR would be ofconsiderable clinical value. Multiple ultrasound functions may be usedto assess MSRs. This systematic approach of using ultrasound to assessthe MSR is a new and unique approach of assessment that carriestremendous diagnostic and patient management potential. Artificialintelligence will be used to improve the accuracy and consistency ofassessing reflexes. Recording of the obtained ultrasound data from amuscle stretch reflex response may include capturing sound, video,images, etc., as known to those of skill in the art.

Further, the present disclosure allows MSR data to be combined withother neuromuscular assessment data such as that from peripheral nerveconduction velocities, electro-myography, tensiomyography, and magneticresonant imaging (MRI) studies, as well as other patient informationsuch as laboratory results, other physical examination findings,concurrent medical conditions, and genetic data for improved diagnosisand management of the patient's condition, such as via treatmentregimens, surgery, medication, physical therapy, etc. This combinationof technology will allow a more precise or personalized approach to themedical practice of individual patients. This patent will furtherenhance medical understanding of MSRs and serve to advance education,research, and clinical practice related to neuromuscular diseases.

In performing the reflex examination, see FIG. 1 , ultrasound device 108may first be used to identify location 102 of the skin over the muscletendon that will be engaged via tool 104, tool 104 may be a reflexhammer or automated adjustable ballistic device as known to those ofskill in the art. Various ultrasound devices 108 can be employed forthis purpose such as handheld, stationary or other styles of ultrasounddevices. Examples include, but are not limited to, devices availablefrom SONOSITE from Fujifilm, VSCAN from GE Healthcare, ACUSON P10 fromSiemens Medical Solutions, VIAMO from Canon Medical Systems, CX50 fromPhilips, and/or POSOUND C3CV available from Hitachi. Ultrasound device108 will then be placed on skin surface 106 over the muscle being tested(not shown) for an optimal image. A muscle stretch reflex will then beelicited in the subject, such as by striking the tendon with tool 104.Ultrasound image loops of several seconds duration can be recorded justprior to striking the muscle tendon continuing through the duration ofthe muscle contraction and return to the previous muscle resting state.Further, ultrasound device 108 may be placed on the subject in multiplepositions, such as shown in FIG. 1 wherein ultrasound device 108 isplaced in a transverse position at (a) and a longitudinal position (b)with respect to location 102.

Four different modes of ultrasound are used in medical imaging. Theseare: A-mode: A-mode is the simplest type of ultrasound. A singletransducer scans a line through the body with the echoes plotted onscreen as a function of depth. Therapeutic ultrasound aimed at aspecific tumor or calculus is also A-mode, to allow for pinpointaccurate focus of the destructive wave energy.

B-mode: In B-mode ultrasound, a linear array of transducerssimultaneously scans a plane through the body that can be viewed as atwo-dimensional image on screen.

M-mode: M stands for motion. In m-mode a rapid sequence of B-mode scanswhose images follow each other in sequence on screen enables doctors tosee and measure range of motion, as the organ boundaries that producereflections move relative to the probe.

Doppler mode: This mode makes use of the Doppler effect in measuring andvisualizing blood flow. Doppler sonography plays an important role inmedicine. Sonography can be enhanced with Doppler measurements, whichemploy the Doppler effect to assess whether structures (usually blood)are moving towards or away from the probe, and its relative velocity. Bycalculating the frequency shift of a particular sample volume, forexample a jet of blood flow over a heart valve, its speed and directioncan be determined and visualized. This is particularly useful incardiovascular studies (sonography of the vasculature system and heart)and essential in many areas such as determining reverse blood flow inthe liver vasculature in portal hypertension. The Doppler information isdisplayed graphically using spectral Doppler, or as an image using colorDoppler (directional Doppler) or power Doppler (non directionalDoppler). This Doppler shift falls in the audible range and is oftenpresented audibly using stereo speakers: this produces a verydistinctive, although synthetic, pulsing sound.

For the current disclosure, recording can include B-mode (brightnessmode) ultrasound scanning that will capture a real-time detailed imageof the anatomical structures of the muscle and surrounding tissue, seeFIG. 2 .

Ultrasound machine calipers will be used to measure to one hundredthcentimeter the difference in muscle dimensions before tapping the tendonand with contraction, see FIG. 7 , showing measurement 702 of the rectusfemoris and 704 of the vastus intermedius at muscle resting state (a)and measurement 706 of the rectus femoris and 708 of the vastusintermedius at muscle reflex response (b).

If available on the ultrasound device, muscle contraction can also berecorded in M-mode which records tissue movement across time, see FIG. 5. This will allow the shape and time of muscle contraction andrelaxation to be precisely assessed, see FIG. 6 , as well as the changein muscle dimensions with contraction, see FIG. 8 . This information hasnot been previously assessed with ultrasound for MSRs and can provideimportant objective diagnostic information. Relaxation or recovery timeof certain reflexes can be helpful in suggesting or establishing medicaldiagnoses. A common example is the slowed relaxation phase ofcontraction of the gastrocnemius muscle in the ankle jerk seen inhypothyroidism. However, the current disclosure is not so limited andapplicable to a host of medical conditions such as, but not limited to,anxiety, Lou Gehrig's disease, multiple sclerosis, Parkinson's disease,stroke, brain injury, or spinal cord injury, etc.

There are several types of Doppler ultrasound scanning. A color Dopplerhelps visualize movement, speed, and direction in color. The resultingimage includes a color overlay showing speed and direction. A duplexDoppler takes a standard image of a structure and graphs the data. Aspectral Doppler shows a structure as graphed data. A continuous-waveDoppler sends a continuous stream of soundwaves, which allows theultrasound to more accurately measure structures moving at fasterspeeds. Power Doppler is a form of color Doppler that is more sensitiveto flow or movement than color Doppler but does not give direction offlow.

For the current disclosure, measurements in the various ultrasoundDoppler modes, which detect direction of motion and/or velocity ofmotion to varying degrees, can also be performed. These include colorDoppler, spectral Doppler, and power Doppler. Although Doppler is usedprimarily to measure blood flow it can provide information on bodytissue movement as well and indicate if the MSR is intact, see FIGS. 3and 4 .

Another order of magnitude of improved reproducibility andstandardization of MSR assessment can be achieved by using an automateddevice capable of delivering a calibrated, focused tap or vibratory blowto the muscle tendon while assessing the MSR with herein describedultrasound applications.

Digital data from the various ultrasound assessment methods of MSRdescribed herein can be combined and analyzed with artificialintelligence developed using supervised and/or unsupervised trainingmethods in patients with disease and adequate controls to significantlyexpand the level of assessment and understanding of an individualpatient's condition. AI in healthcare and medicine means using data moreeffectively through machine learning algorithms to produce positivepatient outcomes.

The sheer amount of data created through IoT-enabled devices, theelectronic medical record (EMR), and ever-expanding quantities ofgenetic data has made possible a large number of applications ofartificial intelligence in healthcare. The underlying value ofartificial intelligence is to enhance human decision-making and automateprocesses that are time- or resource-intensive for humans to perform.This promise relies on data—capturing it, analyzing, and using it toprovide precise, data-driven answers to critical questions.

Prediction forms a core component of what healthcare professionals doevery day. AI can operate as a fast, accurate, and in the long run,cost-effective method to assist human experience and intuition throughpredictive analytics. AI is not meant to replace doctors, but ratherempower healthcare professionals by adding a data-driven context thatdelivers the right information at the right time, allowing them to makemore informed decisions.

Healthcare applications that leverage artificial intelligence can beused to make more accurate diagnoses, identify at-risk populations,manage and assign administrative resources, forecast the potential valueof research projects, and better understand how patients will respond tomedicines and treatment protocols.

In addition, ultrasound assessment data can be combined with otherneuromuscular assessment data such as peripheral nerve conductionvelocities and electromyography results as well as other patientinformation such as pertinent laboratory results, physical examinationmeasurements, genetic data, and magnetic resident imaging (MRI) andanalyzed with artificial intelligence algorithms and deep learning tonot only improve individual patient care but also advance ourunderstanding of neuromuscular diseases and other conditions affectingthe MSRs.

Novel elements of this disclosure include:

1. Determining objective measurements of muscle stretch reflexes.

2. The use of ultrasound to assess muscle stretch reflexes.

3. The use of ultrasound B-mode to assess muscle stretch reflexes.

4. The use of ultrasound M-mode to assess muscle stretch reflexes.

5. The use of ultrasound Doppler (color, spectral, and power) to assessmuscle stretch reflexes.

6. The use of artificial intelligence to assess muscle stretch reflexes.

7. Combining muscle stretch reflex data with other patient data withartificial intelligence to enhance patient diagnoses and management.

8. Combining an automated adjustable ballistic tendon device withultrasound assessment of muscle stretch reflexes.

Ultrasound can be used to assist with the physical examination of musclestretch reflexes or deep tendon reflexes such as the knee jerk.Objective data can be obtained that add value to the examination andassist with diagnosis and management of patients with neuromusculardiseases and other conditions that affect the neuromuscular system.

At present, the examiner's estimate of muscle stretch reflexes onphysical examination is highly subjective. This subjective approachseverely limits the value of MSRs in diagnosing and managing patientswith possible neuromuscular diseases or neuromuscular effects from otherdiseases or trauma.

This disclosure will dramatically improve on the subjective nature ofreflex data. It will provide visual, measurable, and repeatable data foranalysis that can be saved for future reference on the patient. Theobjective data will also be amenable to artificial intelligence analysisindependently and in combination with other patient data. Havingobjective repeatable reflex data will dramatically advance the value ofthe reflex assessment and fundamentally change the clinical approach tothe patient neuromuscular examination.

The applications for this approach to reflex assessment would be quitelarge. Tendon reflex examination is standard for a comprehensivephysical examination, standard for a neurological examination, and usedfor many common diseases and medical conditions that can affect theneuromuscular system and the muscle stretch reflex. These would includenearly all neurological and muscular conditions and many conditions thatcan affect the MSR such as diabetes, hypothyroidism, eclampsia,herniated disc disease, etc. Thus, there will be many clinicians,including almost all physicians as well as nurses and physicianassistants, who would be interested in this ultrasound/AI reflexexamination approach. There is an ever-expanding number of ultrasoundmanufacturers that would be interested in such an ultrasound applicationfor their ultrasound systems.

There will be a number of competitive advantages for those companieslicensing this disclosure and virtually all ultrasound manufacturerswill likely be interested. Advantages include ultrasound systems havinga new application that provides a marked improvement in patientassessment of a commonly performed component of the physicalexamination. This can provide an objective, recordable assessment ofmuscle contraction that will enhance patient diagnosis as well asmanagement and ongoing assessment of the patient. This will also be avaluable clinical and basic science research tool for studyingneuro-muscular and other diseases. For those teaching neuro-muscularphysiology, pathophysiology, and the physical examination thisdisclosure will likewise be of great value by providing valuableeducational materials and hands-on laboratory teaching opportunities ofthe physical examination and neuromuscular diseases for a broad array oflearners.

This disclosure could also lead to further development of neuromuscularassessment laboratories that could provide greater services and generateadditional revenue for performing a more comprehensive assessment of allMSRs.

FIG. 1 shows at (a) an ultrasound scanning probe in the transverseposition (across the short axis of the muscle length) over the rectusfemoris and vastus intermedius muscles of the quadriceps muscle whiletapping the patellar tendon with a reflex hammer. At (b), the scanningprobe is in the longitudinal position (along the long axis of the musclelength).

FIG. 2 show a transverse view of B-mode (brightness mode) ultrasoundimage identifying the rectus femoris and vastus intermedius muscles andthe femur bone of the upper leg beneath the ultrasound probe.

FIG. 3 is a transverse view of spectral Doppler-mode image with thesample area in the vastus intermedius as the patellar tendon is struckwith a reflex hammer resulting in a chirping sound indicating the MSR isintact. The sound coincides with the biphasic or triphasic waveform dueto the velocity and direction of muscle contraction and relaxation. Thetendon was struck twice giving two sets of contractions and spectralDoppler waves.

FIG. 4 is the same as FIG. 3 except with the probe in the longitudinalorientation.

FIG. 5 is a transverse view using M-mode (motion mode) ultrasoundwherein the sampling line is in the middle of the rectus femoris andvastus intermedius muscles. On the top half of the figure is a B-modeimage with the sampling line which represents a narrow ultrasound sliceof the tissue that is shown in the bottom half of the figure acrosstime. In practice this is viewed as a video sample of the slice acrosstime. The various levels of tissue in the thin slice from thesubcutaneous tissue just under the ultrasound probe down to the femurare identified in the figure. With striking of the patellar tendon witha reflex hammer the muscle will contract and then relax. The motion ofmuscle contraction and relaxation are detected across time andvisualized in the lower half of the figure. The sudden clip indicatedmuscle contraction with striking of the muscle tendon. The patellatendon was struck twice during this time period.

FIG. 6 shows M-mode calculation of the speed of contraction, relaxation,and total duration of the reflex which are calculated by the ultrasoundsystem after a video segment is saved and calipers are used to identifythe points of interest. Distance and velocity results are displayed inthe measurement box in the upper left position of the figure. For thefirst reflex, the time for full contraction was 0.067 sec with avelocity of 13.95 cm/sec. Relaxation of the first reflex took 0.433 secat a velocity of 2.15 cm/sec. The total time for the second reflex fromthe initial contraction through full relaxation back to resting statewas 0.320 seconds.

FIG. 7 shows B-mode and caliper markings used to measure change inmuscle size of the rectus femoris and vastus intermedius muscles in alongitudinal view from resting state at (a) to contraction (thickening)at (b) during a reflex response. Rectus femoris increased from 0.81 cmat rest to 0.86 cm with contraction. Vastus intermedius increased from1.37 cm at rest to 1.75 cm with contraction.

FIG. 8 shows M-mode assessment measurement of the vastus intermediusmuscle in a longitudinal view from the resting state (1.15 cm) tocontraction (1.82 cm maximum thickness between the white arrows) duringa reflex response.

Various modifications and variations of the described methods,pharmaceutical compositions, and kits of the disclosure will be apparentto those skilled in the art without departing from the scope and spiritof the disclosure. Although the disclosure has been described inconnection with specific embodiments, it will be understood that it iscapable of further modifications and that the disclosure as claimedshould not be unduly limited to such specific embodiments. Indeed,various modifications of the described modes for carrying out thedisclosure that are obvious to those skilled in the art are intended tobe within the scope of the disclosure. This application is intended tocover any variations, uses, or adaptations of the disclosure following,in general, the principles of the disclosure and including suchdepartures from the present disclosure come within known customarypractice within the art to which the disclosure pertains and may beapplied to the essential features herein before set forth.

What is claimed is:
 1. A method for improved muscle stretch reflexassessments comprising: eliciting at least one muscle stretch reflexresponse in a subject to analyze neurological and muscular components ofthe at least one muscle stretch reflex response; employing at least oneultrasound device to analyze the subject while the muscle stretch reflexresponse occurs via measuring at least one muscle dimension withultrasound machine calipers; obtaining muscle stretch reflex dataregarding the at least one muscle stretch reflex response for thesubject wherein the muscle stretch reflex data includes measuring the atleast one muscle dimension with ultrasound machine calipers beforeeliciting at least one muscle stretch reflex response and measuring atleast one muscle dimension with ultrasound machine calipers when musclecontraction occurs due to eliciting the at least one muscle stretchreflex; analyzing the muscle stretch reflex data to determine a healthcondition of the subject by; comparing the at least one muscle dimensionobtained prior to the at least one muscle stretch reflex response withthe at least one muscle dimension obtained during the at least onemuscle stretch reflex; and analyzing: activation of at least one stretchreceptor in at least one muscle spindle, at least one sensory nerveimpulse from the at least one stretch receptor to at least one spinalcord synapse with at least one motor neuron; and at least one motornerve impulse from the at least one spinal cord synapse.
 2. The methodof claim 1, further comprising recording the muscle stretch reflex dataobtained from the subject.
 3. The method of claim 1, wherein a computeror processor uses at least one artificial intelligence algorithm toanalyze the muscle stretch reflex data.
 4. The method of claim 1,further comprising diagnosing a medical condition indicated via themuscle stretch reflex data obtained from the subject.
 5. The method ofclaim 1, further comprising combining the muscle stretch reflex datawith at least one other neuromuscular assessment data obtained from atleast one physical examination.
 6. The method of claim 5, wherein the atleast one other neuromuscular assessment data comprises peripheral nerveconduction velocities, electromyography, tensiomyography, or magneticresonant imaging.
 7. The method of claim 1, further comprising analyzingthe muscle stretch reflex data in conjunction with separately obtainedlaboratory genetic information of the subject.
 8. The method of claim 1,further comprising employing the muscle stretch reflex data to manage amedical condition in the subject.
 9. The method of claim 1, wherein theultrasound function analyzes the subject prior to, during, and afterelicitation of the muscle stretch reflex response.
 10. The method ofclaim 1, further comprising measuring presence and magnitude of themuscle stretch reflex response.
 11. A new ultrasound analysis techniquecomprising: eliciting at least one muscle stretch reflex response in asubject; employing an ultrasound device in either A Mode, B Mode, M Modeor Doppler Mode to analyze the subject while the muscle stretch reflexresponse occurs; obtaining muscle stretch reflex data regarding the atleast one muscle stretch reflex response for the subject; obtainingmuscle stretch reflex data regarding the at least one muscle stretchreflex response for the subject wherein the muscle stretch reflex dataincludes measuring the at least one muscle dimension with ultrasoundmachine calipers before eliciting at least one muscle stretch reflexresponse and measuring at least one muscle dimension with ultrasoundmachine calipers when muscle contraction occurs due to eliciting the atleast one muscle stretch reflex; and analyzing the muscle stretch reflexdata to determine a health condition of the subject by; comparing the atleast one muscle dimension obtained prior to the at least one musclestretch reflex response with the at least one muscle dimension obtainedduring the at least one muscle stretch reflex; and analyzing: activationof at least one stretch receptor in at least one muscle spindle, atleast one sensory nerve impulse from the at least one stretch receptorto at least one spinal cord synapse with at least one motor neuron; andat least one motor nerve impulse from the at least one spinal cordsynapse.
 12. The technique of claim 11, further comprising recording themuscle stretch reflex data obtained from the subject.
 13. The techniqueof claim 11, wherein a computer or processor uses at least oneartificial intelligence algorithm to analyze the muscle stretch reflexdata.
 14. The technique of claim 11, further comprising diagnosing amedical condition indicated via the muscle stretch reflex data obtainedfrom the subject.
 15. The technique of claim 11, further comprisingcombining the muscle stretch reflex data with at least one otherneuromuscular assessment data obtained from at least one physicalexamination.
 16. The technique of claim 15, wherein the at least oneother neuromuscular assessment data comprises peripheral nerveconduction velocities, electromyography, tensiomyography, or magneticresonant imaging.
 17. The technique of claim 11, further comprisinganalyzing the muscle stretch reflex data in conjunction with separatelyobtained laboratory genetic information of the subject.
 18. Thetechnique of claim 11, further comprising employing the muscle stretchreflex data to manage a medical condition in the subject.
 19. Thetechnique of claim 11, wherein the ultrasound device analyzes thesubject prior to, during, and after elicitation of the muscle stretchreflex response.
 20. The technique of claim 11, further comprisingmeasuring presence and magnitude of the at least one muscle stretchreflex response by analyzing muscle size changes during the at least onemuscle stretch reflex response.